I've been in data and engineering for a long time now, long enough to remember when "big data" meant standing up a Hadoop cluster and hoping your ops team could keep it alive. Long enough, too, to have watched more than one wave of "we're finally solving data silos" move through the industry, with ...

Over the past couple of years, I have worked with education and edtech clients across the UK, Europe and the US. In that time, I have seen the AI conversation in education become louder, but not always clearer. It often comes back to two questions: are students using AI to cheat, and are ...

For a decade, boardrooms heard that data was "the new oil." That framing has quietly expired. Oil sits in a barrel and holds its value. Data sitting in a warehouse does the opposite, it decays, drifts and duplicates. In 2026, data only creates value once it's been refined and fed into the systems ...

Notes from a closed-door ClairX roundtable with senior UK and European enterprise leaders on what actually stands between AI pilots and accountable production systems. We recently brought together senior leaders for a closed-door roundtable: CIOs, heads of transformation, and risk and governance ...

AI is moving from experimentation into the core of business operations. Generative AI is already changing how teams create, analyse, automate, and support decisions. Agentic AI goes a step further: it can plan, call tools, trigger workflows, and act across systems with increasing autonomy. That ...

Why a single procurement tender says more about the state of enterprise AI than any trend report — and the operating-model gap it exposes. At ClairX, we analyse dozens of AI and automation procurement notices every quarter. It's a habit most people in our line of work would call niche, if not ...

For years, "Responsible AI" was a phrase relegated to policy documents and aspirational manifestos. But in 2026, the conversation shifted. As enterprise adoption moves from isolated sandboxes to production-grade systems, whether deploying traditional machine learning, Generative AI, or autonomous ...

Enterprises don’t become “agent-ready” by picking the right framework or model; they become agent-ready when they consistently choose the right problems, have data and architecture that can support them, and can run automation in production with guardrails and ROI. In practice, this is how a ...